Biomedical image analysis

In recent years, increasing resolving power and automation of biomedical imaging systems have resulted in an exponential growth of the image data. Manual analysis of these data sets is extremely labor intensive and hampers the objectivity and reproducibility of results. Hence, there is a growing need for automatic image processing and analysis methods. In CMVS, our aim has been to apply modern computer vision techniques to biomedical image analysis which is one of our emerging research areas.

Since 2008, we have carried out  some research on  texture-based methods for analyzing microscopic and x-ray images, and for classifying HEp-2 cell images.

In CMVS, we have been also investigating  computer vision based methods for analyzing living cells from microscopic images and videos since 2011. During this time we have had several joint projects, and one of those, Algorithm-based Combination and Analysis of Multidimensional Video and Open Data (ABCdata, 2012-2015), was a strategic opening project funded by the Finnish Funding Agency for Innovation (Tekes). We develop computer vision based methods for analyzing living cells from microscopic images and videos, and offer solutions that can,

  • detect and segment individual objects or particles,
  • model their shapes and morphology,
  • track their movement across the image sequences, and
  • detect events or anomalies based on the features computed from the data.

Contact

Professor Janne Heikkilä

Professor Matti Pietikäinen

 

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Last updated: 31.10.2017